scholarly journals Statistical analysis of flash flood events for designing water harvesting systems in an extremely arid environment

2021 ◽  
Vol 35 (9) ◽  
Author(s):  
Koichi Unami ◽  
Osama Mohawesh ◽  
Rasha M. Fadhil
2021 ◽  
Vol 12 (1-2) ◽  
pp. 117-125
Author(s):  
S Mondal ◽  
L Akter ◽  
HJ Hiya ◽  
MA Farukh

The Sunamganj district is covered by major Haor systems in the north-eastern region of Bangladesh. Flash flood is the most commonly occurring water related disaster in the Haor areas. During the flash flood it is very common that people lost their primary agricultural productions which are the only source of their livelihood. The present study focuses on the effects of 2017 early flash flooding on rice and fish production of Sunamganj Haor areas. The flood caused enormous damage to agriculture such as rice especially Boro rice and fish production on which the Haor dwellers rely upon for their livelihood. The total affected land of Boro rice cultivation in Haors of Sunamganj was 149,224 hectare and the total amount of damaged rice was 393,855 metric ton (MT). The total number of affected farmers was 315,084. The early flash flood also affects the quality of Haor water which caused the death of fishes. The total amount of damaged fish was 49.75 MT and the loss was 158.70 lakh taka. The total number of affected fishermen was 44,445. This findings could be very useful for the environmental scientists to predict the probable future effects on agricultural production due to early flash flood events in Sunamganj Haors areas. Environ. Sci. & Natural Resources, 12(1&2): 117-125, 2019


Author(s):  
G Stancalie ◽  
B Antonescu ◽  
C Oprea ◽  
A Irimescu ◽  
S Catana ◽  
...  

Author(s):  
M Velasco ◽  
A Cabello ◽  
I Escaler ◽  
J Barredo ◽  
A Barrera-Escoda

2017 ◽  
Vol 17 (9) ◽  
pp. 1631-1651 ◽  
Author(s):  
Saif Shabou ◽  
Isabelle Ruin ◽  
Céline Lutoff ◽  
Samuel Debionne ◽  
Sandrine Anquetin ◽  
...  

Abstract. Recent flash flood impact studies highlight that road networks are often disrupted due to adverse weather and flash flood events. Road users are thus particularly exposed to road flooding during their daily mobility. Previous exposure studies, however, do not take into consideration population mobility. Recent advances in transportation research provide an appropriate framework for simulating individual travel-activity patterns using an activity-based approach. These activity-based mobility models enable the prediction of the sequence of activities performed by individuals and locating them with a high spatial–temporal resolution. This paper describes the development of the MobRISK microsimulation system: a model for assessing the exposure of road users to extreme hydrometeorological events. MobRISK aims at providing an accurate spatiotemporal exposure assessment by integrating travel-activity behaviors and mobility adaptation with respect to weather disruptions. The model is applied in a flash-flood-prone area in southern France to assess motorists' exposure to the September 2002 flash flood event. The results show that risk of flooding mainly occurs in principal road links with considerable traffic load. However, a lag time between the timing of the road submersion and persons crossing these roads contributes to reducing the potential vehicle-related fatal accidents. It is also found that sociodemographic variables have a significant effect on individual exposure. Thus, the proposed model demonstrates the benefits of considering spatiotemporal dynamics of population exposure to flash floods and presents an important improvement in exposure assessment methods. Such improved characterization of road user exposures can present valuable information for flood risk management services.


2021 ◽  
Author(s):  
Mohamed Abd-el-Kader ◽  
Ahmed Elfeky ◽  
Mohamed Saber ◽  
Maged AlHarbi ◽  
abed Alataway

Abstract Flash floods are highly devastating, however there is no effective management for their water in Saudi Arabia, therefore, it is crucial to adopt Rainfall Water Harvesting (RWH) techniques to mitigate the flash floods and manage the available water resources from the infrequent and rare rainfall storms. The goal of this study is to create a potential flood hazard map and a map of suitable locations for RWH in Wadi Nisah, Saudi Arabia for future water management and flood prevention plans and to identify potential areas for rainwater harvesting and dam construction for both a flood mitigation and water harvesting. This research was carried out using a spatiotemporal distributed model based on multi-criteria decision analysis by combining Geographic Information System (GIS), Remote Sensing (RS), and Multi-Criteria Decision-Making tools (MCDM). The flood hazard mapping criteria were elevation, drainage density, slope, direct runoff depth at 50 years return period, Topographic witness index, and Curve Number, according to the Multi-criteria decision analysis, while the criteria for RWH were Slope, Land cover, Stream order, Lineaments density, and Average of annual max-24hr Rainfall. The weight of each criteria was estimated based on Analytical Hierarchy Process (AHP). In multi-criteria decision analysis, 21.55 % of the total area for Wadi Nisah was classified as extremely dangerous and dangerous; 65.29 % of the total area was classified as moderate; and 13.15 % of the total area was classified as safe and very safe in flash flood hazard classes. Only 15% of Wadi Nisah has a very high potentiality for RWH and 27.7%, 57.31% of the basin has a moderate and a low or extremely low potentiality of RWH, respectively. According to the developed RWH potentiality map, two possible dam sites were proposed. The maximum height of the proposed dams, which corresponded to the cross section of dam locations, ranged from 6.2 to 9 meters; the maximum width of dams ranged from 573.48 to 725 meters; the maximum storage capacity of reservoirs, which corresponded to the distribution of topographic conditions in the surrounding area, ranged from 3976104.499 m3 to 4328509.123 m3; and the maximum surface area of reservoirs ranged from 1268372.625 m2 to 1505825.676.14 m2. These results are highly important for the decision makers for not only flash flood mitigation but also water management in the study area.


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